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The Decision Maker's Ultimate Guide to MBSE
The Decision Maker's Ultimate Guide to MBSE
The Decision Maker's Ultimate Guide to MBSE
Ebook70 pages40 minutes

The Decision Maker's Ultimate Guide to MBSE

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Business decision makers will face many dilemmas when trying to assess the value that Model-Based Systems Engineering (MBSE) can potentially bring to their organization. Unaided by those who have charted the path before them, they’ll face many pitfalls. The Decision Maker’s Ultimate Guide to MBSE exposes the dilemmas and pitfalls to avoid. It explains how MBSE affects the bottom line offering insights into the sophisticated activity of determining the ROI of implementing MBSE in your environment.

The author leans on two decades of consulting practice serving corporate customers in business sectors, defense, aerospace and technology innovation industries. The decision maker’s guide is for technical executives and managers who want to successfully create their MBSE adoption strategy by making business sense out of MBSE. It is also for technical champions who struggle to make a strong business case for introducing MBSE into their environment.

LanguageEnglish
Release dateJul 1, 2015
ISBN9781310260407
The Decision Maker's Ultimate Guide to MBSE
Author

Ernest Stambouly

Ernest Stambouly is a business professional who leads by inspiring others to perform and achieve their potential in highly challenging environments and competitive markets.Born in 1962, he immigrated to Southern California in 1987 to pursue a Masters in Computer Science. He spent the first decade of his career in a technical position, then chose to pursue a different career serving human potential in the corporate world and local community. He became a business technology consultant for large enterprises, coach for highly performing teams, counselor for small-business entrepreneurs, and executive coach for established non-profit organizations in Orange County, California.As an author, the focus of his writing is to help individuals and businesses join the digital revolution by modernizing their practices, changing the way they conduct business, and themselves, to leverage digital technology for greater returns.Being an accomplished music composer and performer, he brings unique competitive value to his clients by drawing on his artistry to create new thinking and practices in professional and social settings.

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    Book preview

    The Decision Maker's Ultimate Guide to MBSE - Ernest Stambouly

    Purpose

    The primary purpose of this short book is to help technology executives and managers make economically grounded decisions with respect to investing in Model-Based Systems Engineering (MBSE) for product development, as well as managing the lifecycle of their products. Throughout two decades of helping large corporations learn, adopt, and apply the model-based approach for systems engineering and enterprise software development, we have recurrently encountered two obstinate challenges. I wrote this book to address these two challenges directly.

    The first challenge is to help non-technical decision makers produce informed assessments of whether MBSE is for them or not. The market for MBSE is, by large, big corporations building large-scale and complex products and systems. The abundance of literature available today about model-based anything is technical in nature, some geared toward technical management, but not much is available – none that I could find – to help businesspeople make decisions grounded in marketplace mechanics and laws of economics for bottom line and competitiveness sake. My experience with practitioners evangelizing and teaching MBSE, including the people I learned from, was such that they could tell you how technically superior the approach is, in their viewpoint, but little could be clearly articulated about its value and whether one can see worthwhile returns by investing into it.

    The second challenge is to overcome ill-guided percepts and beliefs about the nature and the difficulty of bringing MBSE into an operational environment. We have encountered countless managers and other decision makers who say they need help with the adoption, but their actions and what they are willing to pay for speaks loudly to the contrary. Their actions favor a do-it-yourself approach that almost always leads to failure for reasons that are clear to us, but understandably obscure to anyone who has not undergone this type of change before. The reasons are located in a knowledge gap that is not technical in nature. Two decades of experience taught us to anticipate the do-it-yourself posture that we inevitably encounter, and ethically focus sales and engagement explanations onto that knowledge gap so that we better serve our customers make grounded decisions.

    This is where you, the decision maker, must insist on a lengthy and diligent sales dialogue that relegates part of the cost of determining appropriateness of the approach to the provider. The sales process becomes a collaborative space for education and coaching, rather than an exercise in endurance and misgiving for dealing with the pressure off being sold to. The mature provider will commit to help you make that determination early in a collaborative sales dialogue. This book is your guide and manual for directing that dialogue.

    What is Model-Based Systems Engineering (MBSE)?

    A Shift from a document-centric to a model-based approach to engineering and managing the lifecycle of complex systems

    Model-Based Systems Engineering (MBSE) is a powerful approach to engineering complex systems. It utilizes rich modeling languages, tools and methods to formally specify system design, analysis and trade-off, requirements, system interfaces, enterprise architecture, and many other aspects of development and engineering.

    Modeling is a power practice that enables engineers and other technical professionals to create abstract yet formal models of the complex systems they intend to design and build. They model the structure, behavior, performance, architecture, requirements and many other artifacts of analysis before

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